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                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
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                            <li class="last"><a href="group__shark__globals.html">Global functions</a></li>
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<div class="textblock">Here is a list of all functions with links to the classes they belong to:</div>

<h3><a id="index_m" name="index_m"></a>- m -</h3><ul>
<li>MAJOR()&#160;:&#160;<a class="el" href="structshark_1_1_shark_1_1_version.html#aaf28eda93dd2d3cfd269fe7f05fd3139">shark::Shark::Version&lt; major, minor, patch &gt;</a></li>
<li>makeIndependent()&#160;:&#160;<a class="el" href="group__shark__globals.html#ga35fb8d4c0cbc2a8bef9ebd974e0cf0fa">shark::Data&lt; Type &gt;</a>, <a class="el" href="group__shark__globals.html#ga5a4a7922424072317ec868221e19e075">shark::LabeledData&lt; InputT, LabelT &gt;</a></li>
<li>markLineForDeletion()&#160;:&#160;<a class="el" href="classshark_1_1_l_r_u_cache.html#a738129f952a28aa14f35c952079d0a7e">shark::LRUCache&lt; T &gt;</a></li>
<li>MarkovChain()&#160;:&#160;<a class="el" href="classshark_1_1_markov_chain.html#a71e522eea7f19e4a6d20833ee72b9caa">shark::MarkovChain&lt; Operator &gt;</a></li>
<li>MarkovPole()&#160;:&#160;<a class="el" href="classshark_1_1benchmarks_1_1_markov_pole.html#aea9cdad5afe30b335c969c5b3c0681bf">shark::benchmarks::MarkovPole&lt; HiddenNeuron, OutputNeuron &gt;</a></li>
<li>mask()&#160;:&#160;<a class="el" href="classshark_1_1_one_norm_regularizer.html#ae2cc2a34ce23591f2c21e660789eceef">shark::OneNormRegularizer&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_two_norm_regularizer.html#a4b761f214564a9ffc804563bd2dd71ed">shark::TwoNormRegularizer&lt; SearchPointType &gt;</a></li>
<li>matrix()&#160;:&#160;<a class="el" href="classshark_1_1_block_matrix2x2.html#a7f56cb780421cdde2a0168d65f6c88d9">shark::BlockMatrix2x2&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_difference_kernel_matrix.html#adefbf742ea14714a2c1db0e59fbc418c">shark::DifferenceKernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_example_modified_kernel_matrix.html#a2ea8da22eee5949c474d329fed8f8ce6">shark::ExampleModifiedKernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_kernel_matrix.html#a8a098cfdca9f397c829b51d7063a6e6b">shark::GaussianKernelMatrix&lt; T, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_matrix.html#ad5365d1a9d11ca1175b6bb35607db6d1">shark::KernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#ad16f3372ed0f7b3aa3c13c5519c7f6a4">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_modified_kernel_matrix.html#a6b981a803575419cc9cc4d312191c170">shark::ModifiedKernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_regularized_kernel_matrix.html#a831a5280628bf93c3725c0998b3e6a94">shark::RegularizedKernelMatrix&lt; InputType, CacheType &gt;</a></li>
<li>maxBucketSize()&#160;:&#160;<a class="el" href="classshark_1_1_tree_construction.html#aa1b255097aa1e7101783b1300b921aad">shark::TreeConstruction</a></li>
<li>maxDelta()&#160;:&#160;<a class="el" href="classshark_1_1_rprop.html#a7ca10945bb7ef8a73f53512ff25a77a1">shark::Rprop&lt; SearchPointType &gt;</a></li>
<li>maxDepth()&#160;:&#160;<a class="el" href="classshark_1_1_tree_construction.html#abb2b42865b60ddf110e4915ab6457373">shark::TreeConstruction</a></li>
<li>maxGainBox()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#a3689cea409b991cc35f58e8cf23ddc00">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
<li>maxGainSimplex()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#a190272c5d5f87ebd96e5efe34b7d5614">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
<li>maxInterval()&#160;:&#160;<a class="el" href="classshark_1_1_line_search.html#acb37384b4218a4e7893c04a7dd8a0594">shark::LineSearch&lt; SearchPointType &gt;</a></li>
<li>MaxIterations()&#160;:&#160;<a class="el" href="classshark_1_1_max_iterations.html#aedf040f407079b94199a7f6fe629f5a4">shark::MaxIterations&lt; ResultSet &gt;</a></li>
<li>maxIterations()&#160;:&#160;<a class="el" href="classshark_1_1_r_v_e_a.html#a7c15e038ac3d45a47426859f9e0c5f40">shark::RVEA</a></li>
<li>maxSize()&#160;:&#160;<a class="el" href="classshark_1_1_l_r_u_cache.html#a54c4f8d27361379cc684a5f3bd0ad2c5">shark::LRUCache&lt; T &gt;</a></li>
<li>mean()&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#a6e5e69ec1872d5633d4eb1c2261d05c4">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a5f3b47eb09cea3761614529ae23281e8">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_c_m_a.html#ae078f86fe38152ef21788d97878dc959">shark::CMA</a>, <a class="el" href="classshark_1_1_cross_entropy_method.html#afd392abee54cf3881c031afa6b375ff9">shark::CrossEntropyMethod</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#ad8dfcc9b50d9bae82eaae02edc4a593b">shark::GaussianLayer</a>, <a class="el" href="classshark_1_1_l_m_c_m_a.html#af03c5c09687c82760dd2c4f94ef4adc4">shark::LMCMA</a>, <a class="el" href="classshark_1_1_normalize_kernel_unit_variance.html#aa7dbe18d207e4fd219bb27dd982c699e">shark::NormalizeKernelUnitVariance&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_p_c_a.html#a752eeeb52e068a200891e1419b367033">shark::PCA</a>, <a class="el" href="classshark_1_1_v_d_c_m_a.html#a046fe17ddb1b6e2991bb89235b7c1ae0">shark::VDCMA</a></li>
<li>meanAndScatter()&#160;:&#160;<a class="el" href="classshark_1_1_fisher_l_d_a.html#ab5f3eb6ed8d527290ef15fb3579c90ec">shark::FisherLDA</a></li>
<li>Median()&#160;:&#160;<a class="el" href="classshark_1_1statistics_1_1_median.html#a974ca465682f8786e8f30b32ec27e1bb">shark::statistics::Median</a></li>
<li>membershipKernel()&#160;:&#160;<a class="el" href="classshark_1_1_centroids.html#a76f29a0b624229842ae413d8538a7e72">shark::Centroids</a></li>
<li>MergingProblemFunction()&#160;:&#160;<a class="el" href="structshark_1_1_merge_budget_maintenance_strategy_3_01_real_vector_01_4_1_1_merging_problem_function.html#a5ab2639b70356a5165bffd26702bc058">shark::MergeBudgetMaintenanceStrategy&lt; RealVector &gt;::MergingProblemFunction</a></li>
<li>minCol()&#160;:&#160;<a class="el" href="structshark_1_1_reference_vector_guided_selection.html#ab44cdfa5f098b005d1033b97dcfa1b17">shark::ReferenceVectorGuidedSelection&lt; IndividualType &gt;</a></li>
<li>minImprovementRatio()&#160;:&#160;<a class="el" href="classshark_1_1_trust_region_newton.html#ab8f33456dca90c87be30f3dea462c123">shark::TrustRegionNewton</a></li>
<li>minImpurity()&#160;:&#160;<a class="el" href="classshark_1_1_r_f_trainer_3_01_real_vector_01_4.html#a0afd1b5c06d9eeea0f09ce75b1c3a160">shark::RFTrainer&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01unsigned_01int_01_4.html#a650e555b24698db9bdc5d01fc764ddb7">shark::RFTrainer&lt; unsigned int &gt;</a></li>
<li>minInterval()&#160;:&#160;<a class="el" href="classshark_1_1_line_search.html#a217ebe008c4c33da50caca40e9d6c1f0">shark::LineSearch&lt; SearchPointType &gt;</a></li>
<li>minMargin()&#160;:&#160;<a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#a7711ed0cef0489dc1bca0a9cb26e12fa">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>MINOR()&#160;:&#160;<a class="el" href="structshark_1_1_shark_1_1_version.html#a06fb8113023fbda0bff520dc0d7df574">shark::Shark::Version&lt; major, minor, patch &gt;</a></li>
<li>MissingFeaturesKernelExpansion()&#160;:&#160;<a class="el" href="classshark_1_1_missing_features_kernel_expansion.html#a502217606f51799af4ec422f33e7687e">shark::MissingFeaturesKernelExpansion&lt; InputType &gt;</a></li>
<li>MissingFeatureSvmTrainer()&#160;:&#160;<a class="el" href="classshark_1_1_missing_feature_svm_trainer.html#a1f97cd8783c3825ece12f9fce998b68c">shark::MissingFeatureSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>mixingRatio()&#160;:&#160;<a class="el" href="classshark_1_1_uniform_crossover.html#aaa07b04fde1227e333212e0f9ee4322a">shark::UniformCrossover</a></li>
<li>MklKernel()&#160;:&#160;<a class="el" href="classshark_1_1_mkl_kernel.html#a00976371c0ee1b13a7798689b459961b">shark::MklKernel&lt; InputType &gt;</a></li>
<li>MNIST()&#160;:&#160;<a class="el" href="classshark_1_1_m_n_i_s_t.html#adf07b955e67ef51c57d6986348bca147">shark::MNIST</a></li>
<li>model()&#160;:&#160;<a class="el" href="classshark_1_1_ensemble.html#ade2b84f506a9ca05c99b048d89a81e49">shark::Ensemble&lt; ModelType, OutputType &gt;</a></li>
<li>modelCSvmParameterDerivative()&#160;:&#160;<a class="el" href="classshark_1_1_c_svm_derivative.html#a2e46e908d670b88e6e5ab32f3482e7d8">shark::CSvmDerivative&lt; InputType, CacheType &gt;</a></li>
<li>ModelKernel()&#160;:&#160;<a class="el" href="classshark_1_1_model_kernel.html#af71afc0fec1e47abcdaa1a64a6504090">shark::ModelKernel&lt; InputType &gt;</a></li>
<li>ModifiedKernelMatrix()&#160;:&#160;<a class="el" href="classshark_1_1_modified_kernel_matrix.html#a030a9f52beb1a743a44d7555a6275618">shark::ModifiedKernelMatrix&lt; InputType, CacheType &gt;</a></li>
<li>MOEAD()&#160;:&#160;<a class="el" href="classshark_1_1_m_o_e_a_d.html#a26b14cfa87bf47238663a65a50b00c47">shark::MOEAD</a></li>
<li>momentum()&#160;:&#160;<a class="el" href="classshark_1_1_steepest_descent.html#a12f98f7bfca8fdc699223acc0764658b">shark::SteepestDescent&lt; SearchPointType &gt;</a></li>
<li>MonomialKernel()&#160;:&#160;<a class="el" href="classshark_1_1_monomial_kernel.html#a805b59b34396af06ba8460ab30c39c5b">shark::MonomialKernel&lt; InputType &gt;</a></li>
<li>move()&#160;:&#160;<a class="el" href="classshark_1_1_double_pole.html#a95065838bc7f6ceb3fa85ae568bc9def">shark::DoublePole</a>, <a class="el" href="classshark_1_1_single_pole.html#a454e9979968b1b6a4c667cde379d1e1f">shark::SinglePole</a></li>
<li>mu()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a5c5cd3173b9aef38c6e113517bd8b3d6">shark::CMA</a>, <a class="el" href="classshark_1_1_c_m_s_a.html#a642aff37e6c37deb3e437cae1fc866a3">shark::CMSA</a>, <a class="el" href="classshark_1_1_indicator_based_m_o_c_m_a.html#a091929f84adc0a2b8f61e7b8f373ec33">shark::IndicatorBasedMOCMA&lt; Indicator &gt;</a>, <a class="el" href="classshark_1_1_indicator_based_real_coded_n_s_g_a_i_i.html#a9ab2565056d761b0a503b635753b92f4">shark::IndicatorBasedRealCodedNSGAII&lt; Indicator &gt;</a>, <a class="el" href="classshark_1_1_indicator_based_steady_state_m_o_c_m_a.html#ad2bc3222846e97663a15d19909331b7b">shark::IndicatorBasedSteadyStateMOCMA&lt; Indicator &gt;</a>, <a class="el" href="classshark_1_1_l_m_c_m_a.html#a185f5f8fa9efd945008d6492f9ad5ae4">shark::LMCMA</a>, <a class="el" href="classshark_1_1_m_o_e_a_d.html#ae2ec88daa05a1730409085ac48ddc456">shark::MOEAD</a>, <a class="el" href="classshark_1_1_r_v_e_a.html#ae55c14d099207526073282c311362554">shark::RVEA</a>, <a class="el" href="classshark_1_1_s_m_s_e_m_o_a.html#a0fd9a5e6ba1b1d0d54ab9ec49dbb49df">shark::SMSEMOA</a>, <a class="el" href="classshark_1_1_v_d_c_m_a.html#aca9a92a95cdf91f4346826ee9f565f14">shark::VDCMA</a></li>
<li>MultiChainApproximator()&#160;:&#160;<a class="el" href="classshark_1_1_multi_chain_approximator.html#ab7a3850de8247c8d9ba308fd434b6365">shark::MultiChainApproximator&lt; MarkovChainType &gt;</a></li>
<li>MultiNomialDistribution()&#160;:&#160;<a class="el" href="classshark_1_1_multi_nomial_distribution.html#aa682441c740b382d8dbecf718bc26815">shark::MultiNomialDistribution</a></li>
<li>MultiObjectiveBenchmark()&#160;:&#160;<a class="el" href="classshark_1_1benchmarks_1_1_multi_objective_benchmark.html#a39645b08e34005008946482748022d64">shark::benchmarks::MultiObjectiveBenchmark&lt; Objectives &gt;</a></li>
<li>multiplyDerivative()&#160;:&#160;<a class="el" href="structshark_1_1_fast_sigmoid_neuron.html#a94d4a892f50313b8117b7fae2a5c58a1">shark::FastSigmoidNeuron</a>, <a class="el" href="structshark_1_1_linear_neuron.html#aa8754b55470e7c9e329d032826970f40">shark::LinearNeuron</a>, <a class="el" href="structshark_1_1_logistic_neuron.html#afd46fbdec2e27d513994850946a6380b">shark::LogisticNeuron</a>, <a class="el" href="structshark_1_1_normalizer_neuron.html#a5fba8a4f118c8652b7069d265580527b">shark::NormalizerNeuron&lt; VectorType &gt;</a>, <a class="el" href="structshark_1_1_rectifier_neuron.html#aa0346706ce48969b5759c117e062442d">shark::RectifierNeuron</a>, <a class="el" href="structshark_1_1_softmax_neuron.html#a8c3076e3fe3b18da00cfcd29e0e0cf79">shark::SoftmaxNeuron&lt; VectorType &gt;</a>, <a class="el" href="structshark_1_1_tanh_neuron.html#a89a6085add59e60b91b2ece71e8831d9">shark::TanhNeuron</a></li>
<li>MultiTaskKernel()&#160;:&#160;<a class="el" href="classshark_1_1_multi_task_kernel.html#a51d1610417a9bb6cc4e71725feb39cac">shark::MultiTaskKernel&lt; InputTypeT &gt;</a></li>
<li>MultiTaskSample()&#160;:&#160;<a class="el" href="structshark_1_1_multi_task_sample.html#afecb3cf980d0792da79889176944ca6b">shark::MultiTaskSample&lt; InputTypeT &gt;</a></li>
<li>MultiVariateNormalDistribution()&#160;:&#160;<a class="el" href="classshark_1_1_multi_variate_normal_distribution.html#a5617396a18a310cb513cf43d593f95de">shark::MultiVariateNormalDistribution</a></li>
<li>MultiVariateNormalDistributionCholesky()&#160;:&#160;<a class="el" href="classshark_1_1_multi_variate_normal_distribution_cholesky.html#a7133de09b7605c17d9f0caa1dff6de58">shark::MultiVariateNormalDistributionCholesky</a></li>
<li>mutate()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a_individual.html#a7cb81d9d266d24f1bfc336da863084f9">shark::CMAIndividual&lt; FitnessType &gt;</a></li>
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